Conditional Hypotheses in Comparative Social Science: Mixed-Method Approaches to Middle-Sized Data Analysis

Conditional Dependence in Longitudinal Data Analysis

Mixed models are widely used to analyze longitudinal data. In their conventional formulation as linear mixed models (LMMs) and generalized LMMs (GLMMs), a commonly indispensable assumption in settings involving longitudinal non-Gaussian data is that the longitudinal observations from subjects are conditionally independent, given subject-specific random effects. Although conventional Gaussian...

Mechanisms and Functional Hypotheses in Social Science

Critics of functional explanations in social science maintain that such explanations are illegitimate unless a mechanism is specified. Others argue that mechanisms are not necessary for causal inference and that functional explanations are a type of causal claim that raise no special difficulties for testing. I show that there is indeed a special problem that confronts testing functional explan...

Potentials and Limitations of Comparative Method in Social Science

Comparison is a common research method with outstanding merits and with widespread application. The aim of this article is to discuss systematically some of the methodological strategies of using this mode of research in social science. To do so a few typologies regarding the functions and leverages of comparative analysis are presented first. In the next step various ways in which comparative ...

Data Analysis Methods in Social Networks

Background and Aim. The promising outlook of easy communication incurring minimum cost has caused social networks to face increasing number of active members each day. These members develop and expand international communication through information sharing including personal information. Thus, big data analysis of social networks provides companies, organizations and governments with ample and ...

Multichannel Sequence Analysis Applied to Social Science Data